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Therapeutic potential of vagal neurostimulation to reduce food intake

迷走神经刺激减少食物摄入的治疗潜力

基本信息

批准号：
10207620
负责人：
LEE E FISHER
金额：
$ 48.22万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2023-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10207620
关键词：
Abdomen Address Adult Adverse effects Affect Anatomy Animals Behavioral Blood Pressure Body Weight Body Weight decreased Cardiovascular Diseases Cardiovascular Physiology Cervical Chemicals Chronic Classification Consumption Data Devices Diabetes Mellitus Distal Duodenum Eating Electric Stimulation Electrodes Emetics Emetine Event Excision FDA approved Feeding behaviors Ferrets Fiber Frequencies Gastric Bypass Gastrointestinal Motility Gastrointestinal Physiology Gastrointestinal tract structure Goals Gold Health Care Costs Hearing Heart Rate Implant Individual Intervention Laboratory Rat Laboratory mice Liquid substance Machine Learning Malignant Neoplasms Measures Modeling Nausea Nausea and Vomiting Non-Insulin-Dependent Diabetes Mellitus Obesity Operative Surgical Procedures Patients Pattern Pharmacology Phenotype Physiological Rattus Refractory Reporting Research Rodent Model Satiation Sensory Signal Transduction Site Sleep Stimulus Stomach Strategic Planning Surface Testing Therapeutic Training United States National Institutes of Health Upper digestive tract structure Vagus nerve structure Vomiting awake behavioral pharmacology cardiovascular effects comorbidity design effective therapy effectiveness evaluation efficacy testing experimental study feeding gastric fundus gastrointestinal gastrointestinal function healthy weight heart rate variability indexing innovation insight learning classifier machine learning algorithm obesity treatment personalized medicine pre-clinical predicting response recruit reduced food intake response side effect support vector machine therapeutic target vagus nerve stimulation weight loss intervention

项目摘要

Obesity affects almost 40% percent of US adults and is associated with high levels of comorbidities, including cancer, cardiovascular disease, and diabetes. Although effective treatments with minimal side effects are lacking, vagus nerve stimulation (VNS) can reduce body weight and suppress feeding behavior. There is little insight, however, into its mechanism and it is unclear whether VNS effects on feeding and body weight result from non-specific side effects, such as nausea. The current application directly addresses these issues by assessing gastrointestinal (GI) myoelectric changes as a potential mechanism for effects of VNS on feeding behavior, while comparing these responses to emetic activation. We plan to accomplish this by using a ferret model, which is a gold-standard for studying emesis, vagus nerve, and GI physiology. We will test the hypothesis that electrical stimulation of the vagus nerve can reduce food intake without triggering indicators of nausea, such as disrupted GI myoelectric responses, retching, and vomiting. We will complete three Aims. Aim 1: Define the individualized GI myoelectric patterns during feeding behavior using machine learning classification. Animals will be implanted with planar electrodes attached to the GI serosal surface from proximal gastric fundus to distal duodenum. We will use machine learning to classify GI myoelectric patterns of meal consumption compared to emetic-related states, including those elicited by intragastric emetine and high amplitude and frequency VNS known to trigger emesis. Aim 2: Test the efficacy of abdominal VNS on reducing meal size without triggering disruptions of GI myoelectric responses, retching, and emesis. Animals will be assessed for effects of abdominal VNS using a variety of stimulus parameters on feeding behavior and multi-site GI myoelectric recordings. Aim 3: Determine the efficacy of cervical VNS in controlling meal size without producing off-target effects (disruptions of GI myoelectric responses, retching, emesis, changes in heart rate, or blood pressure). We will test the impact of cervical VNS parameters on feeding behavior, GI myoelectric responses, retching, emesis, hear rate variability, and blood pressure. Our approach is innovative because we will use machine learning classification to detect individualized GI myoelectric response patterns in an awake free-moving animal for comparing therapeutic and off-target effects of VNS on feeding, GI activity, emesis, and cardiovascular function. This planned research is significant because VNS therapy can potentially provide a frontline treatment option for patients with high levels of obesity refractory to behavioral or pharmacological therapy, which unlike other surgical interventions for weight loss, such as gastric bypass, is potentially tunable and reversible by changing stimulation parameters, switching the device off, or complete removal.

肥胖影响了近40%的美国成年人，并与高水平的合并症有关，包括